Code generation
Does the code do what the task asked, and is it actually right?
Solutions · Flagship
Coding and reasoning agents produce work a generic annotator can't judge. Our engineers assess code generation, debugging, architecture, security, reasoning, tool use and task completion — the things that decide whether an agent is trustworthy in production.
Evaluation dimensions
Every trajectory is reviewed against the signals that actually predict whether an agent is safe and useful — by people who could have written the task themselves.
Does the code do what the task asked, and is it actually right?
Can the agent locate and fix the real fault, not a symptom?
Can the agent reason across a whole codebase, not just isolated snippets?
Are tool and function calls correct, sequenced and safe?
Did the agent reach a finished, verifiable end state?
Are the structure and design decisions sound under load?
Does the output introduce vulnerabilities or unsafe patterns?
Does it recognize and surface its own failure modes and limits?
Workflow
A disciplined loop: run representative tasks, have engineers evaluate them, score against your rubric, and hand back signal you can ship on.
We run your agent against real, representative tasks spanning the difficulty range you care about.
Engineers review each trajectory — code, reasoning, tool calls and outcome — not surface fluency.
Judgments are mapped to your rubric, with reasoning attached to every score and flag.
You get per-signal breakdowns and failure modes you can act on, not a single opaque number.
A coding or reasoning agent fails in ways only an engineer recognizes — a subtly wrong refactor, an insecure dependency, a confident answer built on a flawed premise. Judging those outcomes is itself an engineering task. We bring the people who can do it, calibrated to your bar.
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